Many users access video content from services having large collections of video content items. Frequently, these collections include video content that has been uploaded by users from various countries and that contains audio content and/or text content in a variety of languages. As such, video content may be served to users that are unlikely to comprehend the content. For some video content, it may be important for these services to present users with video content that contain audio and/or text content in a language that the user can comprehend.
These services, however, often rely on information that may or may not correctly identify a language used in the video content, such as information in metadata or information provided by a user that uploaded the video content. Moreover, in many instances, the language associated with the video content has not been indicated by the user that uploaded the video content. Techniques, such as automatic speech recognition (ASR), may sometimes be used to determine a language of the video content. Such recognition techniques, however, are not supported for all languages and have problems with background music, noise and multi-party conversations, etc. in the video content. Thus, it is difficult to identify the language of video content.
Accordingly, it is desirable to provide new methods, systems, and media for language identification of a media content item based on comments.